Systemic immune-inflammation index in germ-cell tumours: search for a biological prognostic biomarker

Systemic immunity-inflammation index is associated with body fat distribution among U.S. adults: evidence from national health and nutrition examination survey 2011-2018

OBJECTIVE

The systemic immunity-inflammation index (SII) is a newly developed biomarker that provides an integrated measure of inflammation in the body. We aim to evaluate the relationship between SII and body fat distribution.

METHODS

Adults from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 were included. The SII was computed using lymphocyte (LC), neutrophil (NC), and platelet (PC) counts as its components. Body fat distribution was assessed by (total, android, gynoid) percentage fat, total abdominal fat area, subcutaneous adipose tissue area, visceral adipose tissue area, and the ratio of visceral to subcutaneous adipose tissue area (V/S ratio). Multivariable weighted linear regression and subgroup analysis were use to examine the relationships between fat distribution and SII. Restricted cubic splines (RCS) and threshold effect analysis were used to examine analyze nonlinear associations.

RESULTS

After exclusions, a total of 11,192 adults with a weighted mean age of 38.46 ± 0.26 years were studied. In multivariable weighted linear regression, each level increase in log2SII was associated with increased of 0.23 SDs total percentage fat (95% CI = 0.03, 0.43) and 0.26 SDs android percentage fat (95% CI = 0.06, 0.47). Besides, the subgroup analysis showed that the positive association between SII and android percentage fat was mainly among obese individuals (BMI > 30 kg/m2) and non-obese individuals without DM or hypertension. Meanwhile, the relationship between SII and the V/S ratio was found to be significant in the female subgroup, the obese subgroup, individuals with non-alcoholic fatty liver disease (NAFLD), and those without diabetes mellitus. Finally, SII exhibited an inverted U-shaped relationship with total percentage fat, android percent fat and total abdominal fat. Accordingly, threshold effect analysis indicated a positive association between lower SII levels and total percentage fat, android percentage fat and total abdominal fat area.

CONCLUSIONS

In the nationwide study, it was observed that the SII exhibited a significant correlation with higher levels of body fat, specifically android fat. This association was particularly noticeable within specific subgroups of the population.

Systemic immune-inflammatory index and its association with female sexual dysfunction, specifically low sexual frequency, in depressive patients: Results from NHANES 2005 to 2016

Sexual dysfunction, particularly in females, is a complex issue influenced by various factors, including depression and inflammation. The Systemic immune-inflammation index (SII), an inflammatory biomarker, has shown associations with different health conditions, but its relationship with female sexual dysfunction (FSD) remains unclear. This study aimed to investigate the association between SII and FSD in the context of depression, utilizing low sexual frequency as an assessment indicator. Data from the National Health and Nutrition Examination Survey (NHANES) 2005 to 2016, involving 1042 depressed female participants, were analyzed. FSD, indicated by low sexual frequency, and SII, derived from complete blood count results, were assessed. Logistic regression and subgroup analyses were conducted, considering demographic and health-related factors. A total of 1042 individuals were included in our analysis; 11.5163% of participants were categorized as having FSD, which decreased with the higher SII tertiles (tertile 1, 13.8329%; tertile 2, 13.5447%; tertile 3, 7.1839%; p for trend < 0.0001). Multivariate linear regression analysis showed a significant negative association between SII and FSD [0.9993 (0.9987, 0.9999)]. This negative association in a subgroup analysis is distinctly and significantly present in the Mexican American subgroup [0.9959 (0.9923, 0.9996)], while it does not reach statistical significance in other racial categories. Furthermore, the association between SII and FSD was nonlinear; using a 2-segment linear regression model, we found a U-shaped relationship between SII and FSD with an inflection point of 2100 (1000 cells/µL). In summary, in depressed individuals, a higher SII is independently associated with a decreased likelihood of FSD, emphasizing the potential role of inflammation in female sexual health.

Exploring the potential relationship between short sleep risks and cognitive function from the perspective of inflammatory biomarkers and cellular pathways: Insights from population-based and mice studies

AIMS

The molecular mechanism of short-sleep conditions on cognition remains largely unknown. This research aimed to investigate associations between short sleep, inflammatory biomarkers and cognitive function in the US population (NHANES data 2011-2014) and explore cellular mechanisms in mice.

METHODS

Systemic immune-inflammation index (SII) was calculated using blood-cell based biomarkers. Further, we employed integrated bioinformatics and single-cell transcriptomics (GSE137665) to examine how short sleep exposure influenced the molecular pathways associated with inflammation in the brain. To explore the signaling pathways and biological processes of sleep deprivation, we carried out enrichment analyses utilizing the GO and KEGG databases.

RESULTS

Population results showed that, compared with normal sleep group, severe short sleep was associated with lower cognitive ability in all the four tests. Moreover, a higher SII level was correlated with lower scores of cognitive tests. In mice study, elevated activation of the inflammatory pathway was observed in cell subgroups of neurons within the sleep deprivation and recovery sleep cohorts. Additionally, heightened expression of oxidative stress and integrated stress response pathways was noted in GABAergic neurons during sleep deprivation.

CONCLUSION

This study contributed to the understanding of the influence of short sleep on cognitive function and its cellular mechanisms.

Association between systemic immune-inflammation index and post-stroke depression: a cross-sectional study of the national health and nutrition examination survey 2005-2020

Background

Less research has linked the Systemic Immune Inflammatory Index (SII) with post-stroke depression (PSD). This study aims to look at any potential connections between SII and PSD.

Methods

The National Health and Nutrition Examination Survey (NHANES), conducted in a population that embodied complete SII and stroke data from 2005 to 2020, was used to perform the current cross-sectional survey. A fitted smoothed curve was used to depict the nonlinear link between SII and PSD, and multiple linear regression analysis demonstrated a positive correlation between SII and PSD.

Results

Multiple linear regression analysis showed that SII and PSD were markedly related [1.11(1.05, 1.17)]. Interaction tests showed that the association between SII and PSD was not statistically different between strata, and age, sex, BMI, income poverty ratio, education level, smoking status, diabetes mellitus, coronary heart disease, and heart failure did not have a significant effect on this positive association (p > 0.05 for interaction). In addition, a nonlinear association between SII and PSD was found using a two-stage linear regression model.

Conclusion

The results of our research support the existence of a significant positive correlation between SII levels and PSD. Further prospective trials are required to comprehend SII, which is for the PSD thoroughly.

Association between systemic immunity-inflammation index and hypertension in US adults from NHANES 1999-2018

Hypertension is a disease closely related to inflammation, and the systemic immunity-inflammation index (SII) is a new and easily detectable inflammatory marker. We aimed to investigate the association between SII and hypertension risk in a adult population in the US. We utilized data from the National Health and Nutrition Examination Survey spanning from 1999 to 2018, incorporating comprehensive information from adults reporting hypertension. This included details on blood pressure monitoring, complete blood cell counts, and standard biochemical results. The SII was computed as the platelet count multiplied by the neutrophil count divided by the lymphocyte count. We employed a weighted multivariate logistic regression model to examine the correlation between SII and hypertension. Subgroup analyses were conducted to explore potential influencing factors. Furthermore, smooth curve fitting and two-piecewise logistic regression analysis were employed to describe non-linear relationships and identify inflection points. This population-based study involved 44,070 adults aged 20-85 years. Following Ln-transformation of the SII, multivariable logistic regression revealed that, in a fully adjusted model, participants in the highest quartile of Ln(SII) had a 12% increased risk of hypertension compared to those in the lowest quartile, which was statistically significant (OR:1.12; 95% CI 1.01, 1.24; P < 0.001), with a P for trend = 0.019. Subgroup analysis indicated no significant interactions between Ln(SII) and specific subgroups except for the body mass index subgroup (all P for interaction > 0.05). Additionally, the association between Ln(SII) and hypertension displayed a U-shaped curve, with an inflection point at 5.89 (1000 cells/μl). Based on this research result, we found a U-shaped correlation between elevated SII levels and hypertension risk in American adults, with a inflection point of 5.89 (1000 cells)/μl). To validate these findings, larger scale prospective surveys are needed to support the results of this study and investigate potential mechanisms.

Association between systemic immune-inflammation index and insulin resistance and mortality

The role of inflammation in disease promotion is significant, yet the precise association between a newly identified inflammatory biomarker and insulin resistance (IR) and mortality remains uncertain. We aim to explore the potential correlation between systemic immune-inflammation index (SII) and these factors. We used data from 2011 to 2016 of National Health and Nutrition Examination Survey, and multivariate logistic regression and restricted cubic spline were employed. Subgroup and interaction analysis were conducted to recognize the consistency of the results. The association between SII and mortality was described by survival analysis. 6734 participants were enrolled, of whom 49.3% (3318) exhibited IR and 7.02% experienced mortality. Multivariate logistic regression revealed that individuals in the highest quartile (Q4) of SII had a significantly increased risk of IR compared to those in the lowest quartile (Q1). We then identified a linear association between SII and IR with an inflection point of 407, but may be influenced by gender. Similarly, compared to Q1, people whose SII at Q4 showed a higher all-cause and cardiovascular mortality. It showed a significant association between SII and both all-cause and cardiovascular mortality, but the results need to be interpreted with caution.

Association between Systemic Immunity-Inflammation Index and Hyperlipidemia: A Population-Based Study from the NHANES (2015-2020)

The systemic immunity-inflammation index (SII) is a novel inflammatory marker, and aberrant blood lipid levels are linked to inflammation. This study aimed to look at the probable link between SII and hyperlipidemia. The current cross-sectional investigation was carried out among people with complete SII and hyperlipidemia data from the 2015-2020 National Health and Nutrition Examination Survey (NHANES). SII was computed by dividing the platelet count × the neutrophil count/the lymphocyte count. The National Cholesterol Education Program standards were used to define hyperlipidemia. The nonlinear association between SII and hyperlipidemia was described using fitted smoothing curves and threshold effect analyses. A total of 6117 US adults were included in our study. A substantial positive correlation between SII and hyperlipidemia was found [1.03 (1.01, 1.05)] in a multivariate linear regression analysis. Age, sex, body mass index, smoking status, hypertension, and diabetes were not significantly correlated with this positive connection, according to subgroup analysis and interaction testing (p for interaction > 0.05). Additionally, we discovered a non-linear association between SII and hyperlipidemia with an inflection point of 479.15 using a two-segment linear regression model. Our findings suggest a significant association between SII levels and hyperlipidemia. More large-scale prospective studies are needed to investigate the role of SII in hyperlipidemia.

Prognostic Significance of Systemic Inflammation Markers in Testicular and Penile Cancer: A Narrative Review of Current Literature

In contemporary clinical practice, biomarkers are indispensable in the assessment and management of oncological patients. Although established serum tumor markers (beta human chorionic gonadotropin (bHCG), alpha fetoprotein (AFP), and lactate dehydrogenase (LDH)) have an indisputably important role in the management of patients with testicular cancer (TC), the application of these tumor markers may be accompanied with certain limitations, implying the need for additional biomarkers. Contrary to TC, there is a lack of established serological biomarkers for penile cancer (PC) and the management of this urological malignancy is based on multiple clinicopathological parameters. Therefore, the identification and rigorous analytical and clinical validation of reliable biomarkers are considered pivotal for improving PC management. Inflammation may be associated with all stages of oncogenesis, from initial neoplastic transformation to angiogenesis, tissue invasion, and metastasis. Accordingly, an array of inflammation-related indices have gained increasing attention as emerging predictors of oncological outcomes. The clinical usefulness of systemic inflammation markers was reported in many urological and non-urological malignancies. The aim of this narrative review is to summarize current scientific data regarding the prognostic and predictive significance of systemic inflammation markers in TC and PC patients.

Identification of novel potential genes in testicular germ cell tumors: A transcriptome analysis

OBJECTIVE

Testicular germ cell tumors (TGCTs), containing pure seminoma and non-seminoma, occupy the most majority of testicular cancers in adolescents and young men, which has increased dramatically in recent decades. Therefore, it is important to find crucial genes for improving diagnosis and prognosis in TGCTs. However, the diagnostic and prognostic markers of TGCTs are limited.

METHODS

In this study, our main objective is to explore novel potential genes that can be used as diagnostic and prognostic biomarkers in TGCTs. Our study detected 732 differentially expressed genes (DEGs) using three microarray expression profiling datasets from Gene Expression Omnibus (GEO). Multiple analysis was performed to identify the roles of DEGs, including pathway and functional enrichment analysis, protein-protein interaction (PPI) network analysis, module analysis, and survival analysis.

RESULT

In total, 322 upregulated genes and 406 downregulated genes were identified as DEGs The functional and pathway enrichment analysis shows that DEGs were highly enriched in multiple biological attributes such as T cell activation, reproduction in multicellular organism, sperm flagellum, antigen processing and presentation Then, seven potential crucial genes were identified via PPI network analysis, module analysis, and survival analysis. Furthermore, 7 potential crucial genes had shown to play a key role in regulating immune cell infiltration level in patients with TGCTs.

CONCLUSION

We identified seven potential crucial genes (LAPTM5, NCF2, PECAM1, CD14, COL4A2, ANPEP and RGS1), which may be molecular markers in improving the way of diagnosis and prognosis in TGCTs.

Does systemic immune inflammation index have predictive value in gastric cancer prognosis?

OBJECTIVE

Some studies have reported that the systemic immune inflammatory index (SII) and neutrophil/lymphocyte ratio (NLR) provide predictive data on prognosis in gastric cancer patients. In the present study, it was aimed to examine the diagnostic and prognostic values of SII and NLR in gastric cancer.

METHODS

A total of 152 patients, operated with the diagnosis of gastric cancer and followed up in the General Surgery Department of our hospital between January 2012 and April 2018, and 152 healthy controls were included in the study.

RESULTS

The mean SII (989±685) and the mean NLR (3.9±5.2) were significantly higher in gastric cancer patients than the healthy control group (433±203 and 1.9±0.8, respectively) (p<0.001 for both). In the receiver operating characteristic analyzes, a threshold value of 892 for SII had a sensitivity of 66.7% and a specificity of 62.7% in terms of predicting 5-year survival (AUC: 0.637; p=0.076; LB: 0.475; UB: 0.799; CI 95%). The 5-year survival rate was found to be significantly higher in those with a SII of above 892 than those with a SII of 892 and below (p=0.026). The 5-year mortality risk was 0.67-fold lower in those with SII above 892 (p=0.111; 95% CI 0.4-1.1).

CONCLUSION

The present study findings show that SII and NLR are far from providing reliable data on gastric cancer prognosis.

Short- and Mid-Term Survival Prediction in Patients with Acute Type A Aortic Dissection Undergoing Surgical Repair: Based on the Systemic Immune-Inflammation Index

Purpose

The postoperative survival of patients with acute type A aortic dissection (aTAAD) remains unsatisfactory. The current study developed an easy-to-use survival prediction model and calculator.

Methods

A total of 496 patients with aTAAD undergoing surgical repair were included in this study. The systemic immune-inflammation index (SII) and other clinical features were collected and subjected to logistic and Cox regression analyses. The survival prediction model was based on Cox regression analyses and exhibited as a nomogram. For convenience of use, the nomogram was further developed into calculator software.

Results

We demonstrated that a higher preoperative SII was associated with in-hospital death (OR: 4.116, p < 0.001) and a higher postoperative overall survival rate (HR: 2.467, p < 0.001) in aTAAD patients undergoing surgical repair. A survival prediction model and calculator based on SII and four other clinical features were developed. The overall C-index of the model was 0.743. The areas under the curves (AUCs) of the 1- and 3-month and 1- and 3-year survival probabilities were 0.73, 0.71, 0.71 and 0.72, respectively. The model also showed good calibration and clinical utility.

Conclusion

Preoperative SII is significantly associated with postoperative survival. Based on SII and other clinical features, we created the first easy-to-use prediction model and calculator for predicting the postoperative survival rate in aTAAD patients, which showed good prediction performance.

Association between SII and hepatic steatosis and liver fibrosis: A population-based study

Background

The systemic immune-inflammation index (SII) is a novel marker of inflammation, and hepatic steatosis and fibrosis are associated with inflammation. This study aimed to investigate the possible relationship between SII and hepatic steatosis and fibrosis.

Methods

The datasets from the National Health and Nutrition Examination Survey (NHANES) 2017–2020 were used in a cross-sectional investigation. Multivariate linear regression models were used to examine the linear connection between SII and controlled attenuation parameter (CAP) and liver stiffness measurement (LSM). Fitted smoothing curves and threshold effect analysis were used to describe the nonlinear relationship.

Results

This population-based study included a total of 6,792 adults aged 18–80 years. In a multivariate linear regression analysis, a significant positive association between SII and CAP was shown [0.006 (0.001, 0.010)]. This positive association in a subgroup analysis was maintained in men [0.011 (0.004, 0.018)] but not in women. Furthermore, the association between SII and CAP was nonlinear; using a two-segment linear regression model, we found an inverted U-shaped relationship between SII and CAP with an inflection point of 687.059 (1,000 cells/µl). The results of the multiple regression analysis showed that the relationship between SII and LSM was not significant (P = 0.263).

Conclusions

Our findings imply that increased SII levels are linked to hepatic steatosis, but SII is not linked to liver fibrosis. To confirm our findings, more large-scale prospective investigations are needed.

Prognostic Roles of Inflammation- and Nutrition-Based Indicators for Female Patients with Cancer

Purpose

The incidence, progression, and prognosis of cancer could be affected by inflammation and nutrition. Female patients have different inflammatory and nutritional states depending on their age and tumor types. It is important to screen for suitable prognostic indicators in female patients with cancer of different ages and tumor types.

Patients and Methods

Baseline clinicopathologic and laboratory characteristics of 1502 female patients with cancer were obtained from a multicenter cohort study. Concordance indices (C-indices) were used to evaluate the prediction accuracy of following inflammation- and nutrition-based indicators: advanced lung cancer inflammation index (ALI), systemic immune inflammation index (SII), modified geriatric nutritional risk index (mGNRI), albumin-to-globulin ratio (AGR), prognostic nutritional index (PNI), lymphocyte-to-C-reactive protein ratio (LCR), controlling nutritional status score (CONUT), modified Glasgow prognostic score (mGPS), and lymphocyte-to-C-reactive protein score (LCS).

Results

The most suitable indicators in different female populations with cancer had C-indices as follows: LCR (0.668; 95% CI, 0.644–0.693) for all females; AGR (0.681; 95% CI, 0.619–0.743) for young females; LCR (0.667; 95% CI, 0.628–0.706) for middle-aged females; ALI (0.597; 95% CI, 0.574–0.620) for elderly females; LCR (0.684; 95% CI, 0.621–0.747) for females with reproductive system cancer; and ALI (0.652; 95% CI, 0.624–0.680) for females with non-reproductive system cancer.

Conclusion

The most suitable indicators for the different female populations with cancer are summarized as follows: LCR for all females, AGR for young females, LCR for middle-aged females, ALI for elderly females, LCR for females with reproductive system cancer, and ALI for females with non-reproductive system cancer.

Predicting 5-Year Progression and Survival Outcomes for Early Stage Non-small Cell Lung Cancer Treated with Stereotactic Ablative Radiation Therapy: Development and Validation of Robust Prognostic Nomograms

PURPOSE

Our purpose was to develop predictive nomograms for overall survival (OS), progression-free survival (PFS), and time-to-progression (TTP) at 5 years in patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR).

METHODS AND MATERIALS

The study cohort included 714 ES-NSCLC patients treated with SABR from 2004-2015 with median follow-up of 59 months, divided into training and testing sets (8:2), with the former used for nomogram development. The least absolute shrinkage and selection operator were initially employed to screen for predictors of OS, PFS, and TTP, and identified predictors were subsequently applied toward Cox proportional hazards regression modeling. Significant predictors (P < .05) on multivariable regression were then used to develop nomograms, which were validated via evaluation of concordance indexes (C-index) and calibration plots. Finally, Kaplan-Meier method and Gray's test were employed to compare and confirm differences in outcomes among various groups and explore prognostic factors associated with local versus distant disease progression.

RESULTS

Significant predictors of both OS and PFS at 5 years included age, sex, Charlson comorbidity index, diffusing capacity of carbon monoxide, systemic immune-inflammation index, and tumor size (P ≤ .01 for all). Eastern Cooperative Oncology Group performance status predicted for OS as well (P = .01), and both tumor size (P < .01) and minimum biological equivalent dose to 95% of planning target volume (PTV D95 BED₁₀; P < .01) were predictive of TTP. The C-indexes for the OS, PFS, and TTP nomograms were 0.73, 0.68, and 0.60 in the training data set and 0.72, 0.66, and 0.59 in the testing data set, respectively. Tumor size > 2.45 cm and PTV D95 BED₁₀ < 113 Gy were significantly associated with both local and distant progression.

CONCLUSIONS

These prognostic nomograms can accurately predict for OS, PFS, and TTP at 5 years after SABR for ES-NSCLC and may thus help identify high-risk patients who could benefit from additional systemic therapy.

Systemic immune-inflammation index is a promising noninvasive marker to predict survival of lung cancer: A meta-analysis

BACKGROUND

The prognostic value of pretreatment systemic immune-inflammation index (SII) in lung cancer has yet to be fully established.

METHODS

Relevant articles were obtained by performing a systematic search. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were used to assess the relationship between SII index and overall survival (OS) in lung cancer; the OS was calculated from the time of cancer diagnosis to the date of death due to any cause or to the last date of follow-up.

RESULTS

In total, 2786 patients with lung cancer from 7 studies were included in this meta-analysis. The median thresholds to define high SII was 640 (range 395.4-1600) in the analyzed studies. The pooled HR for OS was 1.77 (95% CI: 1.54-2.00, P < .001), suggesting that the patients with a high SII score had a worse OS. In addition, results from subgroup meta-analysis showed the significant prognostic significance of SII in lung cancer. Especially, the predictive value of SII was significant in the multivariable model for NSCLC (HR: 1.97, 95% CI: 1.69-2.25, P < .001; 5 studies, 1746 patients), and SCLC (HR: 1.38, 95% CI: 1.02-1.85, P < .001; 1 study, 919 patients).

CONCLUSION

Our data suggest that high SII index indicates poor survival rate in lung cancer. Further researches are warranted to verify the significance of SII index in clinical practice.

Preoperative systemic immune-inflammation index predicts prognosis of patients with oral squamous cell carcinoma after curative resection

Background

Deregulated inflammation and immune deficit both intricately associate with cancer initiation and progression, which have been increasingly exploited as prognostic biomarkers and therapeutic targets. Recently, systemic immune-inflammation index (SII) based on peripheral neutrophil, lymphocyte and platelet counts serves as a novel and powerful cancer biomarker with prognostic significance in multiple types of malignancies. Here, we sought to evaluate the prognostic value of preoperative SII in patients with primary oral squamous cell carcinoma (OSCC) after curative resection.

Methods

Two independent cohorts with a total number of 309 patients with OSCC from two tertiary referral hospitals were included and defined as training (Nanjing, 138) and validation (Wuxi, 171) cohort, respectively. Preoperative SII in both cohorts was calculated and its optimal cutoff value was initially determined by X-tile software in the training cohort and then verified in the validation cohort.

Results

Our data indicated that high SII (≥ 484.5) was significantly associated with larger tumor size (P < 0.05, Chi square test), reduced overall and disease-free survival (Kaplan–Meir, P < 0.05, Log-rank test). Univariate and multivariate analyses further revealed that SII was an independent prognostic predictor for patient survival. Moreover, the area under receiver operating characteristic curve of SII for survival was significantly greater or comparable to other well-established prognostic parameters, indicative of its satisfactory prediction accuracy and specificity.

Conclusions

Our findings reveal that high preoperative SII associates with poor outcome and serves as a non-invasive, low-cost and powerful prognostic predictor for patients with OSCC. This inflammation/immune-related biomarker holds translational potentials to supplement currently prognostic regime to better stratification of patients and treatment planning.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1742-x) contains supplementary material, which is available to authorized users.